Building an Arabic Transliterator and Annotating Data Morphologically. Using Weka to Annotate our Arabic Corpus Morphologically and Compare it with the Xerox Arabic Analyser's Results.

      Аннотация: In this book, we, firstly, discuss related works to ours. Secondly, we create a transliteration program, produce our own corpus, use the Xerox Arabic analyser to morphologically annotate a raw Arabic text, use Weka to train our transliterated corpus, and then, compare the annotation of the Xerox analyser with the results of Weka. The book shows the methods used to create our own transliteration system using a dictionary which maps the Arabic letters with the Latin letters. To do that, we use a raw Arabic text taken from a chapter of the book "Al-Bidayah Wan-Nihayah" for Ibn Kathir and store the results for a later use. the book progresses to discuss the use of the same original text, used previously for transliteration, in the Xerox Arabic analyser which uses a finite-state transducer to annotate the text morphologically. The annotations are, then, selected manually (gold-standard), added to our transliterated text and trained using different algorithms in Weka. Ultimately, the results of Weka are compared with the gold-standard annotation.

Ключевые слова: IT, Linguistic, Corpus, Machine Learning, AI, NLP, Natural Language Processing